Influences of assembly pressure and flow channel size on performances of proton exchange membrane fuel cells based on a multi-model

In this work, assembly pressure and flow channel size on proton exchange membrane fuel cell performance are optimized by means of a multi-model. Based on stress-strain data of the SGL-22BB GDL obtained from its initial compression experiments, Young's modulus with different ranges of assembly pressure fits well through modeling. A mechanical model is established to analyze influences of assembly pressure on various gas diffusion layer parameters. Moreover, a CFD calculation model with different assembly pressures, channel width, and channel depth are established to calculate PEMFC performances. Furthermore, a BP neural network model is utilized to explore optimal combination of assembly pressure, channel width and channel depth. Finally, the CFD model is used to validate effect of size optimization on PEMFC performance. Results indicate that gap change of GDL below bipolar ribs is more remarkable than that below channels under action of the assembly pressure, making liquid water easily transported under high porosity, which is conducive to liquid water to the channels, reduces the accumulation of liquid water under the ribs, and enhances water removal in the PEMFC. Affected by the assembly force, change of GDL porosity affects its diffusion rate, permeability and other parameters, which is not conducive to mass transfer in GDL. Optimizing the depth and different dimensions through width of the flow field can effectively compensate for this effect. Therefore, the PEMFC performance can be enhanced through the comprehensive optimization of the assembly force, flow channel width and flow channel depth. The optimal parameter is obtained when assembly pressure, channel width and channel depth are set as 0.6 MPa, 0.8 mm, and 0.8 mm, respectively. The parameter optimization enhances the mass transfer, impedance, and electrochemical characteristics of PEMFC. Besides, it effectively enhances the quality transfer efficiency inside GDL, prevents flooding, and reduces concentration loss and ohmic loss.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

Applications of sketches in network traffic measurement: A survey

Accurate and timely network traffic measurement is essential for network status monitoring, network fault analysis, network intrusion detection, and network security management. With the rapid development of the network, massive network traffic brings severe challenges to network traffic measurement. However, existing measurement methods suffer from many limitations for effectively recording and accurately analyzing big-volume traffic. Recently, sketches, a family of probabilistic data structures that employ hashing technology for summarizing traffic data, have been widely used to solve these problems. However, current literature still lacks a thorough review on sketch-based traffic measurement methods to offer a comprehensive insight on how to apply sketches for fulfilling various traffic measurement tasks. In this paper, we provide a detailed and comprehensive review on the applications of sketches in network traffic measurement. To this end, we classify the network traffic measurement tasks into four categories based on the target of traffic measurement, namely cardinality estimation, flow size estimation, change anomaly detection, and persistent spreader identification. First, we briefly introduce these four types of traffic measurement tasks and discuss the advantages of applying sketches. Then, we propose a series of requirements with regard to the applications of sketches in network traffic measurement. After that, we perform a fine-grained classification for each sketch-based measurement category according to the technologies applied on sketches. During the review, we evaluate the performance, advantages and disadvantages of current sketch-based traffic measurement methods based on the proposed requirements. Through the thorough review, we gain a number of valuable implications that can guide us to choose and design proper traffic measurement methods based on sketches. We also review a number of general sketches that are highly expected in modern network systems to simultaneously perform multiple traffic measurement tasks and discuss their performance based on the proposed requirements. Finally, through our serious review, we summarize a number of open issues and identify several promising research directions.     

Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region

Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (F_PED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

High-surface-area mesoporous silica-yttria-zirconia ceramic materials prepared by coprecipitation method ― the role of silicon

A high surface area is one of desired properties for yttria-zirconia (Y₂O₃–ZrO₂) ceramic materials given their catalytic applications. The objective of this study is to develop high-surface-area Y₂O₃–ZrO₂ materials by silicon (Si) modification and investigate the role of Si. Si-modified yttrium-zirconium hydroxides were prepared via a one-step precipitation process and calcined at 800 or 950 °C to form Si-modified Y₂O₃–ZrO₂ (denoted as SiO₂–Y₂O₃–ZrO₂) materials containing 0-20 wt% Si as SiO₂. These hydroxides or materials were characterized by ²⁹Si NMR, XPS, TG-DSC, XRD, UV Raman, TEM, and N₂ physisorption measurements. Si species uniformly distributed in the hydroxides tended to be enriched on the material surface at high temperatures. These Si species dominated by the silicates blocked the migration of Y and Zr atoms, which resisted the crystallite growth of Y₂O₃–ZrO₂ components and reduced their crystallite size. Therefore, the SiO₂–Y₂O₃–ZrO₂ possessed a surface area of 59-112 m²/g after calcination at 950 °C for 9 h, which was significantly higher than that of the Y₂O₃–ZrO₂ (23 m²/g). This study may stimulate ideas for developing high-surface-area crystalline ceramic materials calcined at high temperatures.     

The effect of particle size distribution on the microstructure and properties of Al2O3 ceramics formed by stereolithography

Stereolithography (SL) shows advantages for preparing alumina-based ceramics with complex structures. The effects of the particle size distribution, which strongly influence the sintering properties in ceramic SL, have not been systematically explored until now. Herein, the influence of the particle size distribution on SL-manufactured alumina ceramics was investigated, including bending strength at room temperature, post-sintering shrinkage, porosity, and microstructural morphology. Seven particle size distributions of alumina ceramics were studied (in μm/μm: 30/5, 20/3, 10/2, 5/2, 5/0.8, 3/0.5, and 2/0.3); a coarse:fine particle ratio of 6:4 was maintained. At the same sintering temperature, the degree of sintering was greater for finer particle sizes. The particle size distribution had a larger influence on flexural strength, porosity and shrinkage than sintering temperature when the particle size distribution difference reached 10-fold but was weaker for 10 μm/2 μm, 5 μm/2 μm and 5 μm/0.8 μm. The sintering shrinkage characteristics of cuboid samples with different particle sizes were studied. The use of coarse particles influenced the accuracy of small-scale samples. When the particle size was comparable to the sample width, such as 30 μm/5 μm and 5 mm, the width shrinkage was consistent with the height shrinkage. When the particle size was much smaller than the sample width, such as 2 μm/0.3 μm and 5 mm, the width shrinkage was consistent with the length shrinkage. The results of this study provide meaningful guidance for future research on applications of SL and precise control of alumina ceramics through particle gradation.     

Grain size effect on microwave dielectric properties of Na2WO4 ceramics prepared by cold sintering process

In this work, cold sintering was adopted to prepare Na₂WO₄ ceramics with different grain sizes ranging from 0.632 μm to 17.825 μm. Their microstructures, complex impedance, and microwave dielectric properties were studied in-depth. It was found that samples with relative densities higher than 92% can be successfully synthesized by cold sintering process at a low temperature of 240 °C. However, their electrical properties have strong dependence on the grain size. Specifically, the resistance of grain boundaries decreases dramatically with the increase of grain sizes, while the quality factor has a positive correlation with the grain sizes of Na₂WO₄ ceramics. Excellent microwave dielectric properties, including permittivity = 5.80, Q × f = 22,000 GHz, and TCF = −70 ppm/°C, are obtained for Na₂WO₄ ceramics with a grain size of 4.477 μm prepared by cold sintering process.